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Logging training |
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Running DummyClassifier() |
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accuracy: 0.846 average_precision: 0.154 roc_auc: 0.500 recall_macro: 0.500 f1_macro: 0.458 |
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=== new best DummyClassifier() (using recall_macro): |
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accuracy: 0.846 average_precision: 0.154 roc_auc: 0.500 recall_macro: 0.500 f1_macro: 0.458 |
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Running GaussianNB() |
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accuracy: 0.469 average_precision: 0.171 roc_auc: 0.646 recall_macro: 0.550 f1_macro: 0.426 |
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=== new best GaussianNB() (using recall_macro): |
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accuracy: 0.469 average_precision: 0.171 roc_auc: 0.646 recall_macro: 0.550 f1_macro: 0.426 |
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Running MultinomialNB() |
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accuracy: 0.826 average_precision: 0.295 roc_auc: 0.680 recall_macro: 0.542 f1_macro: 0.547 |
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Running DecisionTreeClassifier(class_weight='balanced', max_depth=1) |
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accuracy: 0.872 average_precision: 0.519 roc_auc: 0.883 recall_macro: 0.883 f1_macro: 0.802 |
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=== new best DecisionTreeClassifier(class_weight='balanced', max_depth=1) (using recall_macro): |
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accuracy: 0.872 average_precision: 0.519 roc_auc: 0.883 recall_macro: 0.883 f1_macro: 0.802 |
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Running DecisionTreeClassifier(class_weight='balanced', max_depth=5) |
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accuracy: 0.885 average_precision: 0.552 roc_auc: 0.822 recall_macro: 0.816 f1_macro: 0.786 |
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Running DecisionTreeClassifier(class_weight='balanced', min_impurity_decrease=0.01) |
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accuracy: 0.882 average_precision: 0.603 roc_auc: 0.800 recall_macro: 0.835 f1_macro: 0.789 |
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Running LogisticRegression(C=0.1, class_weight='balanced', max_iter=1000) |
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accuracy: 0.903 average_precision: 0.782 roc_auc: 0.066 recall_macro: 0.854 f1_macro: 0.820 |
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Running LogisticRegression(C=1, class_weight='balanced', max_iter=1000) |
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accuracy: 0.913 average_precision: 0.762 roc_auc: 0.083 recall_macro: 0.853 f1_macro: 0.834 |
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Best model: |
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DecisionTreeClassifier(class_weight='balanced', max_depth=1) |
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Best Scores: |
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accuracy: 0.872 average_precision: 0.519 roc_auc: 0.883 recall_macro: 0.883 f1_macro: 0.802 |
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